Are Human Development, Economic Growth, and the Status of Females Interrelated?

The third goal of the United Nations’eight Millennium Development Goals is to “em-power women and promote equality between men and women” (MDGs, cf. United Nations2000). Although politicians, stakeholders, and researchers alike would ar-gue that the link between overall development and specific gender issues remains

Fig. 11.1 Framework for analysis by indicators

poorly understood and insufficiently addressed (cf. Buvinic and King2007), much has changed over the last half-century in how the subject is approached. When Es-ter Boserup first illustrated the mutual relationship between the status of women and development, the Millennium Development Goals did not exist to support her claims. This did not dissuade her from arguing that understanding the role that women play within a society is essential to understanding the overall development of that society. She showed that besides women’s reproductive work, the agricultural labour performed by women is especially crucial to societies’ economic develop-ment (Boserup1970, 1986, see also Chap. 8 by Ringhofer et al. in this volume).

Boserup integrated these deliberations into her multidisciplinary approach cutting across issues of population, agriculture, and technology (see Boserup1970, among others). Ester Boserup’s theory was unique given the manner in which she integrated women into her fundamental theory of economic change. Her model has stimulated a number of research initiatives and international declarations on the status of women.

In fact, her scholarship laid some of the groundwork for the inclusion of equality between men and women throughout the MDGs.

Although it is not always cited, Boserup’s model continues to be highly influential in the discourse on women and development within the concepts of gender and development (GAD) and even gender mainstreaming.

In a contribution for the International Monetary Fund (IMF), Buvinic and King (2007) illustrated the relationships between gender equality and economic perfor-mance, arguing that “leveling the field of opportunities” through greater gender equality would have impacts at the household, economy and market, and society lev-els and thereby enhance aggregate economic performance both in terms of poverty reduction and economic growth.

We understand the hypothesis put forth by Buvinic and King as an expression of Boserup’s theories on the relationships between the status of women and devel-opment and therefore use it as a reference to test this proposed relationship in the context of Sub-Saharan Africa. In Fig.11.1, we have sketched out the framework of our analysis. We use the UN’s Gender Inequality Index (GII, data source: UNDP 2010) as an indicator reflecting the degree of gender inequality. This indicator cov-ers three dimensions: reproductive health, labour market, and empowerment. These

dimensions coincide well with the spheres for improvement as illustrated by Buvinic and King: household, economy and markets, and society. A GII of 1 represents total inequality, while a GII of 0 represents total equality. We have chosen to further exam-ine the role of the total fertility rate (TFR), as it is not among the indicators included in the GII (data source: United Nations2010a). By definition, the TFR is the average number of children that would be born alive to a woman during her lifetime if she was to pass through her childbearing years (15–49) conforming to the age-specific fertility rates of a given year. As measures of aggregate performance, we examined overall GDP growth, per capita GDP, as well as the Human Development Index (HDI) (data source: UNDP2010; United Nations2010b). The HDI consists of three components: income per capita (GNP per capita in US dollars at purchasing power parity), educational attainment measured by literacy rate and combined enrolment ratio, and longevity measured by life expectancy. In the following analysis, we tested whether there is a relationship between the status of females within a society and that society’s overall performance in terms of human development and economic performance (as postulated by Buvinic and King2007) in Sub-Saharan Africa. For this purpose, the aforementioned indicators were compared and contrasted for a total of 48 Sub-Saharan countries at different points in time, spanning the period from 1995 to 2005. The indicators taken into account were the Human Development In-dex (HDI), the Gender Inequality InIn-dex (GII), the Total Fertility Rate (TFR), and the Gross Domestic Product (GDP) in absolute and per capita terms.

Initially, we examined the relationship between GII and GDP in absolute terms as well as GDP growth as indicators of overall economic performance. We found no systematic relation between these indicators for the Sub-Saharan African coun-tries examined. Councoun-tries with different levels of gender inequality achieved similar rates of GDP growth. Almost the same total GDP could be achieved by countries where gender inequality was similar to European countries (e.g., Mauritius) and by countries in which gender inequality was even higher than the Sub-Saharan average of 0.65 (e.g., Democratic Republic of Congo). Considering the differences between countries across Sub-Saharan Africa, it would have been quite surprising to find a correlation between GII and GDP or GDP growth, especially because economies that are similar in terms of GDP or GDP growth may be very different in terms of population. We therefore decided to focus on GDP per capita (GDP/cap) as a more comparable measure of economic performance. All correlations were checked for statistical significance.¹

For the years 2000 and 2005, we found significant correlations between GDP/cap, total fertility rate, the Gender Inequality Index, and the Human Development In-dex among Sub-Saharan African countries (see Fig.11.2). As was described above, GDP is a component of the HDI, and therefore, this correlation cannot be tested for significance.

We also found a negative correlation between per capita GDP and both the total fertility rate and the Gender Inequality Index: The higher the number of births per woman and the higher the gender inequality, the lower the GDP per capita was in 2000. This very important result illustrates that the high rates of overall GDP growth,

1All correlations shown in the following were tested for a significance level ofα=1 %.

2000

GDP/cap (current USD)

TFR 95-00 (births/woma

n) GII 2000 HDI 2000

2005

GDP/cap (current USD)

TFR 00-05 (births/woma

n) GII 2005 HDI 2005

GDP/cap

(current USD) 1.00- 0.74 - 0.64 0.85

GDP/cap

(current USD) 1.00 - 0.70- 0.65 0.28 TFR 95-00

(births/woma

n) 1.00 0.68 - 0.87

TFR 00-05 (births/woma

n) 1.00 0.70- 0.82

GII 2000 1.00 - 0.62 GI I2005 1.00- 0.70

Fig. 11.2 Correlation coefficients for 2000 and 2005 Fig. 11.3 Relationship

between GDP (in current US$) per capita and GII (N=17;a) and GDP per capita and TFR (N=48;

b) for a selection of Sub-Saharan African Countries in 2000

which are exhibited by many of the countries of Sub-Saharan Africa, do not benefit the population. As shown in Fig.11.3, the majority of countries exhibit fairly low per capita GDP, which is in turn coupled with high GII and TFR.

Figure11.3shows the per capita GDP in the countries of Sub-Saharan Africa in relation to the GII (Fig.11.3a) and to TFR (Fig.11.3b). The clustering on the left-hand side of both diagrams illustrates the relatively low per capita GDP in almost all countries of this region. This low economic wealth can be associated with both high gender inequality (e.g. Niger) and relatively low gender inequality (e.g. Rwanda).

However, it must be noted that the GII levels analysed here were well above the world average (0.5) and significantly higher than the European average (approximately 0.3).

Fig. 11.4 Relationship between GII and TFR for a selection of Sub-Saharan African countries in 2000 (N=17;a) and 2005 (N=48;b)

The three countries in which GII approached the world average in 2000 (Namibia, South Africa, and Botswana) were also the countries with the highest per capita GDP. The total fertility rate also varies considerably amongst those countries with a low per capita GDP and ranges from more than 7 to less than 4 children per woman (Fig.11.3b). The majority of countries in the investigated region had a TFR of 5 or more births per woman between 1995 and 2000. During this same period, the world average TFR was below 3, and the European fertility rate was below 2.

Again, those countries with a noticeably lower TFR (South Africa, Botswana, Gabon, and Mauritius) were also those exhibiting higher GDP/cap values. If we relate the total fertility rate to fertility decisions for countries of Sub-Saharan Africa, we can find evidence that the relationship between women’s status at the household level (or family level, in Boserup’s terms), their say in fertility decisions, and overall economic performance is worth investigating further.

The relationships analysed between the total fertility rate and the gender inequality index showed a significant positive correlation (see Fig.11.4). In the year 2000 (Fig.11.4a), those countries with a high fertility rate were also likely to exhibit a high level of gender inequality, with the highest level of gender inequality in 2000 (GII=0.82) occurring in the country with the highest 1995–2000 TFR (7.7). This